Triple
T14028493
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harry Sinden |
E337525
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Harry
Harry is the given name of Harry Sinden, a notable Canadian former ice hockey coach and executive.
|
E1074834
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Harry | Statement: [Harry Sinden, givenName, Harry]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Harry Context triple: [Harry Sinden, givenName, Harry]
-
A.
Harry
Harry is the given name of Harry S. Truman, the 33rd president of the United States who led the country through the end of World War II and the beginning of the Cold War.
-
B.
Harry
Harry is the given name of Harry Augustus Garfield, an American lawyer, academic, and public official who served as the first head of the U.S. Fuel Administration during World War I.
-
C.
Harry
Harry is the given name of Harry Gregson-Williams, a prominent British film composer and music producer known for his work on numerous Hollywood soundtracks.
-
D.
Harry
Harry is the given name of Harry Dent, an American financial author and economic forecaster known for his controversial market predictions.
-
E.
Harry
Harry is the given first name of Major League Baseball manager and former pitcher Bud Black.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Harry Triple: [Harry Sinden, givenName, Harry]
Generated description
Harry is the given name of Harry Sinden, a notable Canadian former ice hockey coach and executive.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Harry Target entity description: Harry is the given name of Harry Sinden, a notable Canadian former ice hockey coach and executive.
-
A.
Harry
Harry is the given first name of legendary American and Canadian football coach Bud Grant, who led the Minnesota Vikings to multiple Super Bowl appearances.
-
B.
Harry
Harry is the given first name of American basketball player and coach Buddy Jeannette.
-
C.
Harry
Harry is the given name of Harry Nyquist, a pioneering engineer and physicist known for foundational contributions to information theory and telecommunications.
-
D.
Harry
Harry is the given name of Harry Nilsson, the influential American singer-songwriter known for hits like "Without You" and "Everybody's Talkin'."
-
E.
Harry
Harry is the given first name of Roy Halladay, the late Hall of Fame Major League Baseball pitcher renowned for his dominance with the Toronto Blue Jays and Philadelphia Phillies.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d81c6543a48190bd5ba93d7419e797 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2fa830ac81908cb7df7c9e81e42a |
completed | April 14, 2026, 12:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fbc335a474819084c310b10e0ded9a |
completed | May 6, 2026, 10:39 p.m. |
| NEDg | Description generation | batch_69fbc51585608190817e9a80666b7740 |
completed | May 6, 2026, 10:47 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fbc57bf4188190aace2c976d842b43 |
completed | May 6, 2026, 10:49 p.m. |
Created at: April 9, 2026, 10:20 p.m.